{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "import matplotlib.pylab as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.style.use('bmh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>5037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>5</td>\n",
       "      <td>5320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>5</td>\n",
       "      <td>5233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "      <td>5232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>5</td>\n",
       "      <td>5268</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  shop_id  item_id\n",
       "0   0        5     5037\n",
       "1   1        5     5320\n",
       "2   2        5     5233\n",
       "3   3        5     5232\n",
       "4   4        5     5268"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_test = pd.read_csv('./test.csv')\n",
    "df_test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID</th>\n",
       "      <th>item_cnt_month</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID  item_cnt_month\n",
       "0   0             0.5\n",
       "1   1             0.5\n",
       "2   2             0.5\n",
       "3   3             0.5\n",
       "4   4             0.5"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_ex = pd.read_csv('./sample_submission.csv')\n",
    "df_ex.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>date_block_num</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_price</th>\n",
       "      <th>item_cnt_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>02.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>59</td>\n",
       "      <td>22154</td>\n",
       "      <td>999.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>03.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2552</td>\n",
       "      <td>899.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>05.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2552</td>\n",
       "      <td>899.00</td>\n",
       "      <td>-1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>06.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2554</td>\n",
       "      <td>1709.05</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>15.01.2013</td>\n",
       "      <td>0</td>\n",
       "      <td>25</td>\n",
       "      <td>2555</td>\n",
       "      <td>1099.00</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         date  date_block_num  shop_id  item_id  item_price  item_cnt_day\n",
       "0  02.01.2013               0       59    22154      999.00           1.0\n",
       "1  03.01.2013               0       25     2552      899.00           1.0\n",
       "2  05.01.2013               0       25     2552      899.00          -1.0\n",
       "3  06.01.2013               0       25     2554     1709.05           1.0\n",
       "4  15.01.2013               0       25     2555     1099.00           1.0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv('./sales_train.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>date_block_num</th>\n",
       "      <th>shop_id</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_price</th>\n",
       "      <th>item_cnt_day</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2935844</th>\n",
       "      <td>10.10.2015</td>\n",
       "      <td>33</td>\n",
       "      <td>25</td>\n",
       "      <td>7409</td>\n",
       "      <td>299.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2935845</th>\n",
       "      <td>09.10.2015</td>\n",
       "      <td>33</td>\n",
       "      <td>25</td>\n",
       "      <td>7460</td>\n",
       "      <td>299.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2935846</th>\n",
       "      <td>14.10.2015</td>\n",
       "      <td>33</td>\n",
       "      <td>25</td>\n",
       "      <td>7459</td>\n",
       "      <td>349.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2935847</th>\n",
       "      <td>22.10.2015</td>\n",
       "      <td>33</td>\n",
       "      <td>25</td>\n",
       "      <td>7440</td>\n",
       "      <td>299.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2935848</th>\n",
       "      <td>03.10.2015</td>\n",
       "      <td>33</td>\n",
       "      <td>25</td>\n",
       "      <td>7460</td>\n",
       "      <td>299.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               date  date_block_num  shop_id  item_id  item_price  \\\n",
       "2935844  10.10.2015              33       25     7409       299.0   \n",
       "2935845  09.10.2015              33       25     7460       299.0   \n",
       "2935846  14.10.2015              33       25     7459       349.0   \n",
       "2935847  22.10.2015              33       25     7440       299.0   \n",
       "2935848  03.10.2015              33       25     7460       299.0   \n",
       "\n",
       "         item_cnt_day  \n",
       "2935844           1.0  \n",
       "2935845           1.0  \n",
       "2935846           1.0  \n",
       "2935847           1.0  \n",
       "2935848           1.0  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc0355fadd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "shop_stats = df['shop_id'].value_counts()\n",
    "plt.figure(figsize=(8,3))\n",
    "sns.barplot(x=shop_stats.index, y=shop_stats.values)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>shop_name</th>\n",
       "      <th>shop_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>!Якутск Орджоникидзе, 56 фран</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>!Якутск ТЦ \"Центральный\" фран</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Адыгея ТЦ \"Мега\"</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Балашиха ТРК \"Октябрь-Киномир\"</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Волжский ТЦ \"Волга Молл\"</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        shop_name  shop_id\n",
       "0   !Якутск Орджоникидзе, 56 фран        0\n",
       "1   !Якутск ТЦ \"Центральный\" фран        1\n",
       "2                Адыгея ТЦ \"Мега\"        2\n",
       "3  Балашиха ТРК \"Октябрь-Киномир\"        3\n",
       "4        Волжский ТЦ \"Волга Молл\"        4"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shop_df = pd.read_csv('./shops.csv')\n",
    "shop_df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "shop_dict = shop_df.to_dict()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Новосибирск ТРЦ \"Галерея Новосибирск\"'"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "shop_dict['shop_name'][36]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "d2f = lambda k: shop_dict['shop_name'][k]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.5/dist-packages/matplotlib/figure.py:402: UserWarning: matplotlib is currently using a non-GUI backend, so cannot show the figure\n",
      "  \"matplotlib is currently using a non-GUI backend, \"\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc03b8fa828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(6,9))\n",
    "sns.barplot(y=list(map(d2f, shop_stats.index)), x=shop_stats.values, ax=ax)\n",
    "ax.set_xlabel('count')\n",
    "fig.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_name</th>\n",
       "      <th>item_id</th>\n",
       "      <th>item_category_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>! ВО ВЛАСТИ НАВАЖДЕНИЯ (ПЛАСТ.)         D</td>\n",
       "      <td>0</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>!ABBYY FineReader 12 Professional Edition Full...</td>\n",
       "      <td>1</td>\n",
       "      <td>76</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>***В ЛУЧАХ СЛАВЫ   (UNV)                    D</td>\n",
       "      <td>2</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>***ГОЛУБАЯ ВОЛНА  (Univ)                      D</td>\n",
       "      <td>3</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>***КОРОБКА (СТЕКЛО)                       D</td>\n",
       "      <td>4</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                           item_name  item_id  \\\n",
       "0          ! ВО ВЛАСТИ НАВАЖДЕНИЯ (ПЛАСТ.)         D        0   \n",
       "1  !ABBYY FineReader 12 Professional Edition Full...        1   \n",
       "2      ***В ЛУЧАХ СЛАВЫ   (UNV)                    D        2   \n",
       "3    ***ГОЛУБАЯ ВОЛНА  (Univ)                      D        3   \n",
       "4        ***КОРОБКА (СТЕКЛО)                       D        4   \n",
       "\n",
       "   item_category_id  \n",
       "0                40  \n",
       "1                76  \n",
       "2                40  \n",
       "3                40  \n",
       "4                40  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_items = pd.read_csv('./items.csv')\n",
    "df_items.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>item_category_name</th>\n",
       "      <th>item_category_id</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PC - Гарнитуры/Наушники</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Аксессуары - PS2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Аксессуары - PS3</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Аксессуары - PS4</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Аксессуары - PSP</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        item_category_name  item_category_id\n",
       "0  PC - Гарнитуры/Наушники                 0\n",
       "1         Аксессуары - PS2                 1\n",
       "2         Аксессуары - PS3                 2\n",
       "3         Аксессуары - PS4                 3\n",
       "4         Аксессуары - PSP                 4"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_cat = pd.read_csv('./item_categories.csv')\n",
    "df_cat.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Комплект \"Microsoft Xbox One 500GB\" + \"Xbox One Kinect (Сенсор)\" + \"Dance Central Spotlight\" + \"Xbox'"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_items['item_name'][13406]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
